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Adding SLEADE algorithm #6

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Merged
hmgomes merged 1 commit into from
Oct 20, 2025
Merged

Adding SLEADE algorithm #6

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26 changes: 16 additions & 10 deletions moa/src/main/java/moa/classifiers/meta/StreamingRandomPatches.java
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Original file line number Diff line number Diff line change
Expand Up @@ -150,14 +150,14 @@ public void trainOnInstanceImpl(Instance instance) {
this.ensemble[i].evaluator.addResult(example, vote.getArrayRef());
// Train using random subspaces without resampling, i.e. all instances are used for training.
if(this.trainingMethodOption.getChosenIndex() == TRAIN_RANDOM_SUBSPACES) {
this.ensemble[i].trainOnInstance(instance,1, this.instancesSeen, this.classifierRandom);
this.ensemble[i].trainOnInstance(instance,1, this.instancesSeen, this.classifierRandom, true);
}
// Train using random patches or resampling, thus we simulate online bagging with poisson(lambda=...)
else {
int k = MiscUtils.poisson(this.lambdaOption.getValue(), this.classifierRandom);
if (k > 0) {
double weight = k;
this.ensemble[i].trainOnInstance(instance, weight, this.instancesSeen, this.classifierRandom);
this.ensemble[i].trainOnInstance(instance, weight, this.instancesSeen, this.classifierRandom, true);
}
}
}
Expand Down Expand Up @@ -202,7 +202,7 @@ protected Measurement[] getModelMeasurementsImpl() {
return null;
}

protected void initEnsemble(Instance instance) {
public void initEnsemble(Instance instance) {
// Init the ensemble.
int ensembleSize = this.ensembleSizeOption.getValue();
this.ensemble = new StreamingRandomPatchesClassifier[ensembleSize];
Expand Down Expand Up @@ -326,7 +326,7 @@ public Classifier[] getSublearners() {
}

public static ArrayList<ArrayList<Integer>> localRandomKCombinations(int k, int length,
int nCombinations, Random random) {
int nCombinations, Random random) {
ArrayList<ArrayList<Integer>> combinations = new ArrayList<>();
for(int i = 0 ; i < nCombinations ; ++i) {
ArrayList<Integer> combination = new ArrayList<>();
Expand Down Expand Up @@ -364,7 +364,7 @@ public static ArrayList<ArrayList<Integer>> allKCombinations(int k, int length)
}

// Inner class representing the base learner of SRP.
protected class StreamingRandomPatchesClassifier {
public class StreamingRandomPatchesClassifier {
public int indexOriginal;
public long createdOn;
public Classifier classifier;
Expand Down Expand Up @@ -512,7 +512,8 @@ public void reset(Instance instance, long instancesSeen, Random random) {
this.classifier.resetLearning();
this.evaluator.reset();
this.createdOn = instancesSeen;
this.driftDetectionMethod = ((ChangeDetector) getPreparedClassOption(this.driftOption)).copy();
if(this.driftOption != null)
this.driftDetectionMethod = ((ChangeDetector) getPreparedClassOption(this.driftOption)).copy();

if(this.subset != null) {
ArrayList<Integer> fIndexes = this.applySubsetResetStrategy(instance, random);
Expand All @@ -530,7 +531,8 @@ public void reset(Instance instance, long instancesSeen, Random random) {
}
}

public void trainOnInstance(Instance instance, double weight, long instancesSeen, Random random) {
public void trainOnInstance(Instance instance, double weight, long instancesSeen,
Random random, boolean updateDriftDetector) {
boolean correctlyClassifies;
// The subset object will be null if we are training with all features
if(this.subset != null) {
Expand All @@ -541,18 +543,18 @@ public void trainOnInstance(Instance instance, double weight, long instancesSeen
this.classifier.trainOnInstance(this.subset.get(0));
correctlyClassifies = this.classifier.correctlyClassifies(this.subset.get(0));
if(this.bkgLearner != null)
this.bkgLearner.trainOnInstance(instance, weight, instancesSeen, random);
this.bkgLearner.trainOnInstance(instance, weight, instancesSeen, random, updateDriftDetector);
}
else {
Instance weightedInstance = instance.copy();
weightedInstance.setWeight(instance.weight() * weight);
this.classifier.trainOnInstance(weightedInstance);
correctlyClassifies = this.classifier.correctlyClassifies(instance);
if(this.bkgLearner != null)
this.bkgLearner.trainOnInstance(instance, weight, instancesSeen, random);
this.bkgLearner.trainOnInstance(instance, weight, instancesSeen, random, updateDriftDetector);
}

if(!this.disableDriftDetector && !this.isBackgroundLearner) {
if(!this.disableDriftDetector && !this.isBackgroundLearner && updateDriftDetector) {

// Check for warning only if useBkgLearner is active
if (!this.disableBkgLearner) {
Expand Down Expand Up @@ -613,4 +615,8 @@ public double[] getVotesForInstance(Instance instance) {
return vote.getArrayRef();
}
}

public StreamingRandomPatchesClassifier[] getEnsembleMembers() {
return this.ensemble;
}
}
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